New ITEM response models: application to school bullying data

04/02/2019
by   Edilberto Cepeda-Cuervo, et al.
0

School bullying victimization is a variable that cannot be measured directly. Taking into account that this variable has a lower bound, given by the absence of bullying victimization, this paper proposes IRT logistic models, where the latent parameter ranges from 0 to ∞ or from 0 to a positive real number R, defining the IRT parameters and proposing an empirical anchor procedure. As the academic abilities and the school bullying victimization can be explained due to associated factors such as habits, sex, socioeconomic level and education level of parents, IRT regression models are proposed to make joint inferences about individual and school characteristic effects. Results from the application of the proposed models to the Bogotá school bullying dataset are presented. The need for testing based in statistical models increases in different fields.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/16/2022

Variable Selection in Latent Regression IRT Models via Knockoffs: An Application to International Large-scale Assessment in Education

International large-scale assessments (ILSAs) play an important role in ...
research
11/09/2021

Determinants of Women's Attitude towards Intimate Partner Violence: Evidence from Bangladesh

Purpose: The purpose of this study is to identify the important determin...
research
05/04/2023

On factor copula-based mixed regression models

In this article, a copula-based method for mixed regression models is pr...
research
07/31/2023

A One-Parameter Diagnostic Classification Model with Familiar Measurement Properties

Diagnostic classification models (DCMs) are psychometric models designed...
research
12/21/2020

Two-directional simultaneous inference for high-dimensional models

This paper proposes a general two directional simultaneous inference (TO...
research
07/11/2022

Differential item functioning via robust scaling

This paper proposes a new method for assessing differential item functio...

Please sign up or login with your details

Forgot password? Click here to reset